962 resultados para MULTIPLE-DOSE PHARMACOKINETICS


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Background Dementia is a chronic illness without cure or effective treatment, which results in declining mental and physical function and assistance from others to manage activities of daily living. Many people with dementia live in long term care facilities, yet research into their quality of life (QoL) was rare until the last decade. Previous studies failed to incorporate important variables related to the facility and care provision or to look closely at the daily lives of residents. This paper presents a protocol for a comprehensive, multi-perspective assessment of QoL of residents with dementia living in long term care in Australia. A secondary aim is investigating the effectiveness of self-report instruments for measuring QoL. Methods The study utilizes a descriptive, mixed methods design to examine how facility, care staff, and resident factors impact QoL. Over 500 residents with dementia from a stratified, random sample of 53 facilities are being recruited. A sub-sample of 12 residents is also taking part in qualitative interviews and observations. Conclusions This national study will provide a broad understanding of factors underlying QoL for residents with dementia in long term care. The present study uses a similar methodology to the US-based Collaborative Studies of Long Term Care (CS-LTC) Dementia Care Study, applying it to the Australian setting.

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A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC) for CO2, SO2, PM10, and BOD. Policy implications for each type of emission are derived based on the results of the EKC using WRI. Finally, we predicted the future emissions trend and regional share of CO2 emissions. We found that East Asia and South Asia will be increasing their emissions share while other major CO2 emitters will still produce large shares of the total global emissions.

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OBJECTIVE Impaired regulation of the hypothalamic-pituitary-adrenal (HPA) axis and hyper-activity of this system have been described in patients with psychosis. Conversely, some psychiatric disorders such as post-traumatic stress disorder (PTSD) are characterised by HPA hypo-activity, which could be related to prior exposure to trauma. This study examined the cortisol response to the administration of low-dose dexamethasone in first-episode psychosis (FEP) patients and its relationship to childhood trauma. METHOD The low-dose (0.25 mg) Dexamethasone Suppression Test (DST) was performed in 21 neuroleptic-naive or minimally treated FEP patients and 20 healthy control participants. Childhood traumatic events were assessed in all participants using the Childhood Trauma Questionnaire (CTQ) and psychiatric symptoms were assessed in patients using standard rating scales. RESULTS FEP patients reported significantly higher rates of childhood trauma compared to controls (p = 0.001) and exhibited lower basal (a.m.) cortisol (p = 0.04) and an increased rate of cortisol hyper-suppression following dexamethasone administration compared to controls (33% (7/21) vs 5% (1/20), respectively; p = 0.04). There were no significant group differences in mean cortisol decline or percent cortisol suppression following the 0.25 mg DST. This study shows for the first time that a subset of patients experiencing their first episode of psychosis display enhanced cortisol suppression. CONCLUSIONS These findings suggest there may be distinct profiles of HPA axis dysfunction in psychosis which should be further explored.

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The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

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Lake Purrumbete maar is located in the intraplate, monogenetic Newer Volcanics Province in southeastern Australia. The extremely large crater of 3000. m in diameter formed on an intersection of two fault lines and comprises at least three coalesced vents. The evolution of these vents is controlled by the interaction of the tectonic setting and the properties of both hard and soft rock aquifers. Lithics in the maar deposits originate from country rock formations less than 300. m deep, indicating that the large size of the crater cannot only be the result of the downwards migration of the explosion foci in a single vent. Vertical crater walls and primary inward dipping beds evidence that the original size of the crater has been largely preserved. Detailed mapping of the facies distributions, the direction of transport of base surges and pyroclastic flows, and the distribution of ballistic block fields, form the basis for the reconstruction of the complex eruption history,which is characterised by alternations of the eruption style between relatively dry and wet phreatomagmatic conditions, and migration of the vent location along tectonic structures. Three temporally separated eruption phases are recognised, each starting at the same crater located directly at the intersection of two local fault lines. Activity then moved quickly to different locations. A significant volcanic hiatus between two of the three phases shows that the magmatic system was reactivated. The enlargement of especially the main crater by both lateral and vertical growth led to the interception of the individual craters and the formation of the large circular crater. Lake Purrumbete maar is an excellent example of how complicated the evolution of large, seemingly simple, circular maar volcanoes can be, and raises the question if these systems are actually monogenetic.

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‘Complexity’ is a term that is increasingly prevalent in conversations about building capacity for 21st Century professional engineers. Society is grappling with the urgent and challenging reality of accommodating seven billion people, meeting needs and innovating lifestyle improvements in ways that do not destroy atmospheric, biological and oceanic systems critical to life. Over the last two decades in particular, engineering educators have been active in attempting to build capacity amongst professionals to deliver ‘sustainable development’ in this rapidly changing global context. However curriculum literature clearly points to a lack of significant progress, with efforts best described as ad hoc and highly varied. Given the limited timeframes for action to curb environmental degradation proposed by scientists and intergovernmental agencies, the authors of this paper propose it is imperative that curriculum renewal towards education for sustainable development proceeds rapidly, systemically, and in a transformational manner. Within this context, the paper discusses the need to consider a multiple track approach to building capacity for 21st Century engineering, including priorities and timeframes for undergraduate and postgraduate curriculum renewal. The paper begins with a contextual discussion of the term complexity and how it relates to life in the 21st Century. The authors then present a whole of system approach for planning and implementing rapid curriculum renewal that addresses the critical roles of several generations of engineering professionals over the next three decades. The paper concludes with observations regarding engaging with this approach in the context of emerging accreditation requirements and existing curriculum renewal frameworks.

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Effectively capturing opportunities requires rapid decision-making. We investigate the speed of opportunity evaluation decisions by focusing on firms' venture termination and venture advancement decisions. Experience, standard operating procedures, and confidence allow firms to make opportunity evaluation decisions faster; we propose that a firm's attentional orientation, as reflected in its project portfolio, limits the number of domains in which these speed-enhancing mechanisms can be developed. Hence firms' decision speed is likely to vary between different types of decisions. Using unique data on 3,269 mineral exploration ventures in the Australian mining industry, we find that firms with a higher degree of attention toward earlier-stage exploration activities are quicker to abandon potential opportunities in early development but slower to do so later, and that such firms are also slower to advance on potential opportunities at all stages compared to firms that focus their attention differently. Market dynamism moderates these relationships, but only with regard to initial evaluation decisions. Our study extends research on decision speed by showing that firms are not necessarily fast or slow regarding all the decisions they make, and by offering an opportunity evaluation framework that recognizes that decision makers can, in fact often do, pursue multiple potential opportunities simultaneously.

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We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles, designed for monitoring degenerative disease effects in clinical neuroscience studies and drug trials. First we used a set of parameterized surfaces to represent the ventricles in a manually labeled set of 9 subjects' MRIs (atlases). We fluidly registered each of these atlases and mesh models to a set of MRIs from 12 Alzheimer's disease (AD) patients and 14 matched healthy elderly subjects, and we averaged the resulting meshes for each of these images. Validation experiments on expert segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease-related alterations monotonically improved as the number of atlases, N, was increased from 1 to 9. We then combined the segmentations with a radial mapping approach to localize ventricular shape differences in patients. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases, and we formulated a statistical stopping criterion to determine the optimal value of N. Anterior horn anomalies in Alzheimer's patients were only detected with the multi-atlas segmentation, which clearly outperformed the standard single-atlas approach.

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Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

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Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.

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Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

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To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

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The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

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Terrestrial ecosystem productivity is widely accepted to be nutrient limited1. Although nitrogen (N) is deemed a key determinant of aboveground net primary production (ANPP)2,3, the prevalence of co-limitation by N and phosphorus (P) is increasingly recognized4,​5,​6,​7,​8. However, the extent to which terrestrial productivity is co-limited by nutrients other than N and P has remained unclear. Here, we report results from a standardized factorial nutrient addition experiment, in which we added N, P and potassium (K) combined with a selection of micronutrients (K+μ), alone or in concert, to 42 grassland sites spanning five continents, and monitored ANPP. Nutrient availability limited productivity at 31 of the 42 grassland sites. And pairwise combinations of N, P, and K+μ co-limited ANPP at 29 of the sites. Nitrogen limitation peaked in cool, high latitude sites. Our findings highlight the importance of less studied nutrients, such as K and micronutrients, for grassland productivity, and point to significant variations in the type and degree of nutrient limitation. We suggest that multiple-nutrient constraints must be considered when assessing the ecosystem-scale consequences of nutrient enrichment.

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This study investigated a potential source of inaccuracy for diode measurements in modulated beams; the effect of diode housing asymmetry on measurement results. The possible effects of diode housing asymmetry on the measurement of steep dose gradients were evaluated by measuring 5x5 cm2 beam profiles, with three cylindrical diodes and two commonly used ionization chambers, with each dosimeter positioned in a 3D scanning water tank with its stem perpendicular to the beam axis (horizontal) and parallel to the direction of scanning. The resulting profiles were used to compare the penumbrae measured with the diode stem pointing into (equivalent to a “stem-first” setup) and out of the field (equivalent to a “stem-last” setup) in order to evaluate the effects of dosimeter alignment and thereby identify the effects of dosimeter asymmetry. The stem-first and stem-last orientations resulted in differences of up to 0.2 mm in the measured 20-80% penumbra widths and differences of up to 0.4 mm in the off axis position of the 90% isodose. These differences, which are smaller than previously reported for older model dosimeters, were apparent in the profile results for both diodes and small volume ionization chambers. As an extension to this study, the practical use of all five dosimeters was exemplified by measuring point doses in IMRT test beams. These measurements showed good agreement (within 2%) between the diodes and the small volume ionization chamber, with all of these dosimeters being able to identify a region 3% under-dosage which was not identified by a larger volume (6 mm diameter) ionization chamber. The results of this work should help to remove some of the barriers to the use of diodes for modulated radiotherapy dosimetry in the future.